{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Running Feature-Importance within Reader-Annotated data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "\n",
      "Using BookNLP folder path from config.py -- /Users/sunyambagga/Desktop/txtLAB-2/minimal-narrativity/booknlp-output-narrativity/\n",
      "PLACE LEXICON has 1560 entries.\n",
      "Loading TMV features from: /Users/sunyambagga/Desktop/txtLAB-2/detecting-narrativity/pickles/combined_hand_annotate_tense_mood_voice_features_lite.pickle\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import cross_validate\n",
    "from sklearn.ensemble import  RandomForestClassifier\n",
    "\n",
    "import data_loader\n",
    "import vectorizer\n",
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_feat_imp(X):\n",
    "    \"\"\"\n",
    "    Returns average feature-importance across 5-fold CV.\n",
    "    \"\"\"\n",
    "    clf = RandomForestClassifier(n_estimators=500, random_state=42, max_depth=None)\n",
    "    output = cross_validate(clf, X, Y, cv=N_FOLDS, scoring='accuracy', return_estimator=True)\n",
    "    print(\"Output accuracy:\", output['test_score'])\n",
    "    importances = [] # take mean feature importance across 5-runs\n",
    "    for estimator in output['estimator']:\n",
    "        importances.append(estimator.feature_importances_)\n",
    "\n",
    "    feat_imp = np.mean(importances, axis=0)\n",
    "    return feat_imp\n",
    "\n",
    "\n",
    "def plot_feature_importance(feature_names, feat_imp, model_type):\n",
    "    data = {'feature_names': feature_names, 'feature_importance': feat_imp}\n",
    "    fi_df = pd.DataFrame(data)\n",
    "\n",
    "    fi_df.sort_values(by=['feature_importance'], ascending=False, inplace=True)\n",
    "\n",
    "    plt.figure(figsize=(10,8))\n",
    "    sns.barplot(x=fi_df.head(40)['feature_importance'], y=fi_df.head(40)['feature_names'])\n",
    "    plt.title('Random Forest: Feature Importance ({})'.format(model_type))\n",
    "    plt.xlabel('Feature Importance')\n",
    "    plt.ylabel('Feature Names')\n",
    "    plt.savefig(path+'figures/feature-importance/'+model_type, dpi=100)\n",
    "    return fi_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "416 416\n"
     ]
    }
   ],
   "source": [
    "N_FOLDS = 5\n",
    "fnames, Y = data_loader.load_annotated_data(threshold=2.5)\n",
    "path = '/Users/sunyambagga/Desktop/txtLAB-2/detecting-narrativity/'\n",
    "feat_path = path + 'feature-importance/readerAnnotated_'\n",
    "print(len(fnames), len(Y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train -- Other: (416, 10) | pos: (416, 36)\n",
      "Test -- Other: (0,) | pos: (0, 36)\n",
      "Combined shape - train: (416, 46) & test: (0,)\n",
      "Output accuracy: [0.73809524 0.73809524 0.72619048 0.82926829 0.75609756]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# For POS-TMV model:\n",
    "model_type = 'pos-tmv'\n",
    "X, _, feature_names = vectorizer.pos_tmv(fnames, [], return_feature_names=True)\n",
    "\n",
    "feat_imp = get_feat_imp(X)\n",
    "fi_df = plot_feature_importance(feature_names, feat_imp, model_type)\n",
    "fi_df.to_csv(feat_path+model_type+'.csv', index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feature Names: ['cc', 'cd', 'dt', 'ex', 'fw', 'in', 'jj', 'jjr', 'jjs', 'lrb', 'ls', 'md', 'nn', 'nnp', 'nnps', 'nns', 'pdt', 'pos', 'prp', 'rb', 'rbr', 'rbs', 'rp', 'rrb', 'sym', 'to', 'uh', 'vb', 'vbd', 'vbg', 'vbn', 'vbp', 'vbz', 'wdt', 'wp', 'wrb']\n",
      "Output accuracy: [0.76190476 0.77380952 0.75       0.82926829 0.7804878 ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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aI5Ls3rZfTVOzcyr7ACTZA7ilqm4ZRXCSJEld6TpJuwj40yTnAZsCn5pmvZuSnA4cAvz5qIKTJEnqSteD2d5XVftPmjd/ivW+WFXvHEE8kiRJvdB1kjbr1tpiC0cclyRJY6+zJK2qrgAeN4P19hp6MJIkST0z53rS7r7uan79yYO6DkNDstUB/9h1CJIkjUTXNw4sVxIHPpMkSaudXidpSULPY5QkSRqG3iVAbU3Pi5J8EjgbWDfJR5KcneTEJFt0HaMkSdKw9S5Ja+0AHFlVT2inz66qXYGTAS84kyRJc15fk7Qrq+rMtn0f99fyHKzv+TtL1+78zahilCRJGpq+JmmTa3cOmlzHc1LtzvWGGJYkSdJo9DVJG7QGsHfbfg3T1/eUJEmaM8ZhnLTbgR2TLAZuoS22LkmSNJf1LkmbXImgqua1zfd0EpAkSVIHepekraq1t9jaUeklSdLYG4dr0iRJklY7c64n7a5rf8bPP7738lfUrHrEm47rOgRJkuYUe9IkSZJ6yCRNkiSph3qTpA3U7DwsyQVJvp1k3SQnJflgkrOSXJxkz65jlSRJGrbeJGmt7YFPVNWOwM3Ay9v5a1XVQuAtWLtTkiStBvqWpF1eVee07cXA/Lb9pSnm/c5g7c4bl9w59CAlSZKGrW9J2mCGdS/333165xTzfmewduem89YZcoiSJEnD17ckTZIkSZikSZIk9VJvBrOdombnh6dY53qmuCZNkiRprulNkjZbHrTlto5+L0mSxp6nOyVJknpozvWk3XHdpZz3qRd1HcZqZec3frXrECRJmnPsSZMkSeohkzRJkqQeMkmTJEnqoZEmaStaRD3Jvkm+kuSbSX6axLqdkiRptdBFT9qKFlFfCLwW2AV4RZIFkzc4WLvzpiV3DTd6SZKkEegiSVvRIurfqaobquqOdp09Jm9wsHbnJvMeNJyoJUmSRqiLJG1Fi6jXpNdPnpYkSZpzxuHGgWcm2TTJusBLgO93HZAkSdKwjcNgtqcBnwW2Az5fVYs6jkeSJGnoRpqkrWQR9Wur6q9muo91t9jOEfAlSdLYG4fTnZIkSaudXp/urKrDgcM7DkOSJGnkep2krYwl113K9w99QddhzDlP3u+ErkOQJGm10vskLcnBwBLgeuDbVXV1txFJkiQN3zhdk7YvsHXXQUiSJI1CL5O0JO9qa3V+F9ihnb0A+FySc9ox0yRJkuas3p3uTLIb8CrgCTTxnU1TKmoRcOBU46Ql2Q/YD+Ahm5q/SZKk8dfHnrQ9geOr6jdVdSuw3EHPBmt3bmztTkmSNAf0MUkD63NKkqTVXB+TtFOAlyZZN8kGwAvb+bcBG3QXliRJ0uj07pq0qjo7ybHAOcCVwKntosOBQ5LcAexeVXd0FKIkSdLQpWpunVlcsGBBLVpkDXZJktR/SRZX1YKplvXxdKckSdJqzyRNkiSph3p3TdqquvX6S/jWfz6v6zDmjGf/+de7DkGSpNVSL3rSkuyVxArekiRJrV4kaZIkSVrayJO0JB9McsDA9MHAbsCGSY5PcmGSQ5KskeRFba3Oc9panpePOl5JkqQudNGTdgywz8D0K4HrgIXAW4GdgG2Bl1XVV6tql6raBTgX+PBUG0yyX5JFSRbdcttdw41ekiRpBEaepFXVj4Atk2yd5PHATcDPgbOq6rKquhc4Gthj4jVJ3g7cUVWfmGabv6vdudEG1u6UJEnjr6u7O48D9ga2oulZgwfW6yyAJE8HXgE8ZWTRSZIkdayrGweOAV5Fk6gd185bmOSRSdagOR16WpJtgE8Cr7QMlCRJWp10kqRV1QU0xdKvqqpftbPPAD4AnA9cDhwP7AtsBhzf3jzgoF2SJGm1YO1OSZKkjli7U5IkacyYpEmSJPXQnKvdefP1l3D8fz+n6zDG3ktf/82uQ5AkabXWeU+adTslSZIeqPMkTZIkSQ800iRtRep2tsuXJPlIkrOTnJhki1HGK0mS1JVR96TNuG5nu3x94Oyq2hU4GThodKFKkiR1Z6RJ2krU7bwPOLZtHzUwfymDBdZvXWKBdUmSNP66uLtzxnU7pzDl/Ko6FDgUYLv5G82t0XklSdJqqYsbB2ZUt3Mgvr3b9msG5kuSJM1pI+9Jq6oLkvyubmeSHbi/budOwCk0dTsBbgd2TLIYuIWlr2eTJEmas3pduzPJkqqatyKvsXanJEkaF9bulCRJGjO9TtJWtBdNkiRprphztTtvuOESPnv4s7sOY2z9yb7f6joESZJET3vSkpzedQySJEld6mWSVlVP6joGSZKkLvUySUuypH3eK8lJSY5L8pMkn0uSruOTJEkatl4maZM8AXgL8FjgUcCTuw1HkiRp+MYhSTurqn5ZVfcB5wDzJ68wWLvzttus3SlJksbfOCRpdw6072WKO1Kr6tCqWlBVCzbY4EGji0ySJGlIxiFJkyRJWu2YpEmSJPVQr2t3rgxrd0qSpHFh7U5JkqQxY5ImSZLUQ3Oudud1N1zCpz9r7c6V8Rd/Yt1OSZL6ovOetLaqwAldxyFJktQnnSdpkiRJeqCRJmlJPpjkgIHpg4HdgA2THJ/kwiSHJFmjXb4kyT8nOTfJmUkeMsp4JUmSujLqnrRjgH0Gpl8JXAcsBN4K7ARsC7ysXb4+cGZVPR44BXjD6EKVJEnqzkiTtKr6EbBlkq2TPB64Cfg5TX3Oy6rqXuBoYI/2JXcBE9erLWaKup2wdO3OJdbulCRJc0AXd3ceB+wNbEXTswYweUTdiem76/7Rdqes2wlN7U7gUIBtHrnR3BqdV5IkrZa6uHHgGOBVNInace28hUke2V6Ltg9wWgdxSZIk9cbIk7SqugDYALiqqn7Vzj4D+ABwPnA5cPyo45IkSeqTTgazraqdBtonASdNs968gfZx3N/zJkmSNKfNuYoDW2y2vSPnS5KksedgtpIkST0053rSrrnxEj5ytLU7V8ZbX20PpCRJfTE2PWlJTm/HV/O6NEmSNOeNTU9aVT2pbe7daSCSJEkjME49aUuSzE9yftexSJIkDdvYJGmSJEmrkzmRpA3W7rzd2p2SJGkOmBNJWlUdWlULqmrB+hs8qOtwJEmSVtmcSNIkSZLmmnFK0mrSsyRJ0pw1Fklaks2AG4GJZ0mSpDmt9+OkJdmapgD7Z4CjgXcsa/2HbLq9I+dLkqSx1/skraquBh7dTv5Tl7FIkiSNSu+TtBV11U2X8O4vPKfrMMbG+17xza5DkCRJUxiLa9ImJFnSdQySJEmjMFZJmiRJ0uqiV6c7k7wOOJBmmI3zgH8APk8Tp+flJEnSaqM3SVqSHYF3AU+uquuTbAocDnyqqo5M8pedBihJkjRCfTrd+TTguKq6HqCqbgSeTDPsBsBnp3vhYO3O39xq7U5JkjT++pSkhamrCSy3wsBg7c71NrR2pyRJGn99StJOBF7ZVhegPd35feBV7fLXdhWYJEnSqPUmSauqC4B/Bk5Oci7wb8Cbgb9M8kNgoy7jkyRJGqXe3DgAUFVHAEdMmr37QPsDIwxHkiSpM71K0mbDQzfZ3lH0JUnS2OvN6U5JkiTdb871pF1x8yW8/nhrd07lv19qD6MkSePCnjRJkqQeMkmTJEnqoZEnaUnmJ7koyWFJLkjy7STrJjkpyQeTnJXk4iR7tuvv2M47J8l5SbYfdcySJEmj1lVP2vbAJ6pqR+Bm4OXt/LWqaiHwFuCgdt7+wL9X1S7AAuCXow5WkiRp1Lq6ceDyqjqnbS8G5rftL00x7wzgXUkeBnypqi6ZvLEk+wH7Aay/xYOHFLIkSdLodNWTdudA+17uTxbvnDyvqj4PvAi4A/hWkqdN3thg7c4HW7tTkiTNAb2/cSDJo4DLqurjwFeBnTsOSZIkaeh6n6QB+wDnJzkHeAxwZMfxSJIkDd3Ir0mrqiuAxw1Mf3iKda6nvSatqt4PvH9E4UmSJPXCnKs4MH/j7R1ZX5Ikjb1xON0pSZK02plzPWmX3Hwlz/3KG7oOoxe+8eLDug5BkiStJHvSJEmSesgkTZIkqYd6l6QleV1bo/PcJJ9N8pAkx7fT5yZ5UtcxSpIkDVuvrklLsiPwLuDJVXV9kk2BTwEnV9VLk6wJzOs0SEmSpBHoVZIGPA04rh0njaq6sS0D9bp2+l7glskvGqzd+eAtzOEkSdL469vpzgC1oi8arN35oA0tsC5JksZf35K0E4FXJtkMoD3deSLwxnZ6zSQbdhifJEnSSPQqSauqC4B/Bk5Oci7wb8Cbgacm+TGwGNixwxAlSZJGom/XpFFVRwBHTJr94i5ikSRJ6krvkrRVtf3G2zjSviRJGnu9Ot0pSZKkxpzrSbvk5qt53pff03UYnfj6S/6p6xAkSdIsGauetCRXJNm86zgkSZKGbaySNEmSpNVFZ0lakvlJfpLkM0nOT/K5JM9I8v0klyRZmGSzJN9O8qMkn6YZ7FaSJGnO67onbTvg34GdgccArwH2AA4E/h44CDitqp4AfBV4REdxSpIkjVTXNw5cXlU/BkhyAXBiVVU7cO389vEygKr6WpKbptrI0rU7LUggSZLGX9c9aXcOtO8bmL6P+xPI5dbyXLp25/qzHKIkSdLodZ2kLc8pwGsBkjwX2KTbcCRJkkaj70naPwJPSXI28Czg5x3HI0mSNBKdXZNWVVcAjxuY3neaZc8aeNnfjCA0SZKkznV948Cs237jrR15X5Ikjb3lnu5M8ookG7Ttdyf5UpJdhx+aJEnS6msmPWnvqaovJNkDeDbwYeBTwBOHGtlKuuTmX/P84z/UdRid+NpL39Z1CJIkaZbM5MaBe9vn5wOfqqqvAA8aXkj3S7JXkhNGsS9JkqQ+mUmSdlVbkumVwNeTrDPD10mSJGklzSTZeiXwLeA5VXUzsCkw6+fVknwwyQED0wcDuwEbJjk+yYVJDkligihJkua85SY8VfUb4FqampoA9wCXDCGWY4B9BqZfCVwHLATeCuwEbEtbJkqSJGkum8ndnQcBfwe8s521NnDUbAdSVT8CtkyydZLHAzfRDF57VlVdVlX3Akdzf7I4GON+SRYlWXTXrbfPdmiSJEkjN5O7O18KPAE4G6Cqrp4YkmMIjgP2Brai6VmDB9bufEAtz6o6FDgUYKPtHrbcWp+SJEl9N5Pru+6qqqJNjpIMs4L5McCraBK149p5C5M8sr0WbR/gtCHuX5IkqRdmkqT9T3t358ZJ3gB8FzhsGMFU1QXABsBVVfWrdvYZwAeA84HLgeOHsW9JkqQ+We7pzqr6cJJnArcCOwD/UFXfGVZAVbXTQPsk4KRh7UuSJKmv0pzJnMGKyYYMJHVVdeOwgloVCxYsqEWLFnUdhiRJ0nIlWVxVC6ZattyetCR/AbwXuAO4DwjN9WmPms0gJUmSdL+Z3N15ILBjVV0/7GBmwyU3X8fzv/TJrsMYia+97IDlryRJksbSTG4c+Bnwm2EHIkmSpPvNpCftncDpSX4A3Dkxs6reNIyAkmwMvKaqVo/uMEmSpCnMJEn7NPB/wI9prkkbto2BAwCTNEmStNqaSZJ2T1X97dAjud8HgG2TnANMDPXxXJqbFd5XVceOMBZJkqROzOSatO+1tTF/L8mmE48hxvQO4GdVtQtwJrAL8HjgGcCHkvze5BcsVbvzliVDDE2SJGk0ZtKT9pr2+Z0D80Y1BMcewNFtcfVrkpwM/AHw1cGVlq7duY21OyVJ0tibScWBR44ikGmkw31LkiR1ZiY9aSR5HPBY4MET86rqyCHFdBtN/U6AU4C/SHIEsCnwFOBtQ9qvJElSb8yk4sBBwF40SdrXaS7iPw0YSpJWVTck+X6S84FvAOcB59KcYn17Vf16GPuVJEnqk+XW7kzyY5oL939UVY9P8hDgM1X1wlEEuKKs3SlJksbFsmp3zuTuzjuq6j7gnrbI+rVYt1OSJGmoZnJN2qK2CsBhwGJgCXDWUKNaBZfedD0v+OJ/dR3GKjvh5X/WdQiSJKlDM7m7c6KK9yFJvglsWFXnDTcsSZKk1du0pzuTPGLyg6Ys1M1te1Yk2SvJCbO1PUmSpLlgWT1pX6O5o3JwrLICtgC2BNYcYlySJEmrtWmTtKraaXA6yXzg72jKM/3LyuwsyQeBK6vqk+30wTTjom2Y5FqRYXsAAB/NSURBVHhgB5qx0Q6oqvuS/Hm7z6uBS4A7q+qvVmbfkiRJ42S5d3cm2T7J4TRjli0GHltV/28l93cMsM/A9CuB64CFwFuBnYBtgZcl2Rp4D/CHwDOBxywjxvtrd95q7U5JkjT+pu1Ja6sMvAvYEfhX4M/bGporrap+lGTLNgHbArgJ+DlwVlVd1u73aJqanfcAJ1fVje38LwCPnma7v6vdufG2863dKUmSxt6yrkk7F/gFzbVpC4GFyf2Xp1XVm1Zyn8cBewNb0fSsQXOt26DJ18JJkiStVpaVpA1roK5jaMZc2xz4I5rr0BYmeSRwJc3p0ENpxmL7aJJNaK5beznw4yHFJEmS1CvLunHgiGHssKouSLIBcFVV/SrJDsAZwAdorkk7BTi+vXHgX4Af0Nw4cCFwyzBikiRJ6pvl1u7sUpJ5VbUkyVrA8cB/VdXxy3qNtTslSdK4WNXanV06OMk5wPnA5cCXO45HkiRpJGZSu7MzVXVg1zFIkiR1YblJWpJHA58CHlJVj0uyM/Ciqnrf0KNbCZfedCMvOO5zXYex0k7Y+7VdhyBJknpgJqc7DwPeCdwN0BZXf9UwgwJIsm+S/2jbL0ny2GHvU5IkqS9mkqStV1VnTZp3zzCCWYaXACZpkiRptTGTJO36JNvSDjibZG/gVyuzsyRvT/Kmtv3RJP/Xtp+e5Kgkr09ycZKTgSe3y54EvAj4UJJz2lgkSZLmtJkkaX8JfBp4TJKrgLcA+6/k/k4B9mzbC4B5SdamKQN1CfCPNMnZM2l7zqrqdOCrwNuqapeq+tnkjS5du/PWlQxNkiSpP5aZpCVZA1hQVc+gqbX5mKrao6quXMn9LQZ2awezvZNmENsFNInb3cBJVXVdVd0FHDvTjVbVoVW1oKoWPGjDDVcyNEmSpP5YZpJWVfcBf9W2b6+q21ZlZ1V1N3AF8HrgdOBU4KnAtsBFPLCGpyRJ0mppJqc7v5PkwCQPT7LpxGMV9nkKcGD7fCrNqdNzgDOBvZJs1p4CfcXAa24DNliFfUqSJI2VmSRpf0ZzXdopNKcrFwOrUnfpVOD3gDOq6hrgt8CpVfUr4GCaU6DfBc4eeM0xwNuS/MgbByRJ0uqg17U7V4a1OyVJ0rhYVu3OmVQceN1U86vqyFUNTJIkSVObSe3OPxhoPxh4Os2pSJM0SZKkIVluklZVfz04nWQj4LNDi2gVXXrTTbzguOO6DmPGTth7765DkCRJPTSTGwcm+w2w/WwHIkmSpPvN5Jq0/+X+8cvWoKkE8IVhBiVJkrS6m8k1aR8eaN8DXFlVv1yVnSaZD3wT+AHwBOBi4HXA7u3+1gJ+CLyxqu5M8gGa+p33AN+uqgNXZf+SJEl9N5PTnc+rqpPbx/er6pdJPjgL+94BOLSqdgZuBf4WOBzYp6p2oknU3tgOnPtSYMd23fdN3pC1OyVJ0lwzkyTtmVPMe+4s7PsXVfX9tn0UzV2jl1fVxe28I4Cn0CRwvwU+k+RlNNfELcXanZIkaa6ZNklL8sYkPwZ2SHLewONy4LxZ2PeMRtGtqnuAhcAXgZfQnCaVJEma05Z1TdrngW8A7wfeMTD/tqq6cRb2/Ygku1fVGcCraUpB/UWS7arqUuBPgJOTzAPWq6qvJzkTuHQW9i1JktRr0yZpVXULcAtNAkWSLWkGs52XZF5V/XwV930R8KdJPg1cAryZpsj6F5JM3DhwCLAp8JUkDwYC/M0q7leSJKn3llu7M8kLgX8DtgauBbYBLqqqHVd6p83dnSdU1eNWdhvTsXanJEkaF8uq3TmTGwfeB/whcHFVPZLmAv/vL/slkiRJWhUzSdLurqobgDWSrFFV3wN2WZWdVtUVw+hFkyRJmitmMpjtze3F+6cCn0tyLc2gsr106U238KLjTug6jAf46t4v6DoESZI0RmbSk/ZimrHJ3kIz/MXPgBcOM6gJSa5Isvko9iVJktQny+1Jq6rbk2wDbF9VRyRZD1hz2IElGfo+JEmS+mq5PWlJ3gAcB3y6nfVQ4Msrs7Mkb0/yprb90ST/17afnuSoJEuSvDfJD2jqeAK8LclZ7WO7ldmvJEnSuJnJ6c6/BJ5MU56JqroE2HIl93cKsGfbXkAz5trawB4017ytD5xfVU+sqtPa9W6tqoXAfwAfW8n9SpIkjZWZJGl3VtVdExPtQLMzKuk0hcXAbkk2AO4EzqBJ1vakSdLupSn/NOjogefdmcLSBdZvWcnQJEmS+mMmSdrJSf4eWDfJM4EvAP+7MjurqruBK4DXA6fTJGZPBbalqUDw26q6d/LLpmkPbnegwPpGKxOaJElSr8wkSXsHcB3wY+AvgK8D716FfZ4CHNg+nwrsD5xT05c+2Gfg+YxV2K8kSdLYmPbuziSPqKqfV9V9wGHtYzacCrwLOKO9c/S37bzprNPeSLAGbR1RSZKkuW7a2p1Jzq6qXdv2F6vq5SONbCVZu1OSJI2Lla3dmYH2o2Y3JEmSJC3LspK05V6wL0mSpOFYVsWBxye5laZHbd22TTtdVbXh0KNbCZfedBsvOe7ErsP4nS/v/fSuQ5AkSWNo2iStqizLJEmS1JGZDMEhSZKkERtakpZkfpKLkhyW5IIk306ybpKTknywrcV5cZI92/X3TfKVJN9M8tMkB7Xz10/ytSTnJjk/yT7L3rMkSdL4W9Y1abNhe+DVVfWGJP8DTAzjsVZVLUzyPOAg4Bnt/IXA44DfAD9M8jVgG+Dqqno+QBJLCkiSpDlv2Kc7L6+qc9r2YmB+2/7SFPMAvlNVN1TVHe06e9BUOnhG2/u2Z1U9oDjn0rU7bx7G+5AkSRqpYSdpdw607+X+nrs7p5gHDxzqo6rqYmA3mmTt/Un+YfJOlq7dufHsRC5JktShYZ/uXFHPTLIpcAfwEuDPkmwN3FhVRyVZAuzbZYCSJEmj0Lck7TTgs8B2wOeralGSZwMfSnIfcDfwxi4DlCRJGoVpa3eOWpJ9gQVV9Versh1rd0qSpHGxsrU7JUmS1JHenO6sqsOBwzsOQ5IkqRd6k6TNlp/ddDsv++KZI9vfl17+hyPblyRJWn14ulOSJKmHTNIkSZJ6qNMkLcnbk7ypbX80yf+17acnOSrJkiQfSXJ2khOTbNFlvJIkSaPSdU/aKcCebXsBMC/J2jTloE4F1gfOrqpdgZNp6nxKkiTNeV0naYuB3ZJsQFMq6gyaZG1PmiTtPuDYdt2jaJK3Bxis3XmntTslSdIc0GmSVlV3A1cArwdOp0nMngpsC1w01Uum2c7vaneuY+1OSZI0B3TdkwbNKc8D2+dTgf2Bc6ophbAGsHe73mtoykZJkiTNeX0YJ+1U4F3AGVV1e5LftvMAbgd2TLIYuAXYp6MYJUmSRqrzJK2qTgTWHph+9KTl7wHeM+q4JEmSutR5kjbbtt1kfasASJKksdeHa9KmVVXzuo5BkiSpC3OuJ+2ym+7gFV+8YOj7+cLLdxz6PiRJ0uqrdz1pSU5PsnWS47qORZIkqSu960mrqie1zb2XuaIkSdIc1seetCVJ5ic5v53eMclZSc5Jcl6S7buOUZIkadh615M2hf2Bf6+qzyV5ELBm1wFJkiQN2zgkaWcA70ryMOBLVXXJ5BWS7AfsB7De5r834vAkSZJmX+9Od05WVZ8HXgTcAXwrydOmWGegducmI49RkiRptvU+SUvyKOCyqvo48FVg545DkiRJGro+Jmk16Xkf4Pwk5wCPAY7sJCpJkqQR6tU1aUk2A24EJp6pqvcD7+8yLkmSpFHrTZKWZGvgJOAzwNHAO1ZmO4/aZF2rAUiSpLHXmyStqq4GHt1O/lOXsUiSJHWtN0nabPnFzXfxpuN/MfT9fPylDx/6PiRJ0uqrjzcOSJIkrfZ6naSl0esYJUmShqF3CVBbt/OiJJ8EzgbuTfKRJGcnOTHJFl3HKEmSNGy9S9JaOwBHVtUT2umzq2pX4GTgoO7CkiRJGo2+JmlXVtWZbfs+4Ni2fRSwx+SVk+yXZFGSRXfceuOoYpQkSRqaviZpty9jWT1gxkDtznU33HSIYUmSJI1GX5O0QWsAe7ft1wCndRiLJEnSSIzDOGm3AzsmWQzcQlPLU5IkaU7rXZJWVVcAj5s07z3AezoJSJIkqQO9S9JW1cM3fpDVACRJ0tjr/TVpVTWv6xgkSZJGbc71pF1z89187PhfD2Xbb3npVkPZriRJ0mS970mTJElaHZmkSZIk9VCvkrQkf5zkrCTnJPl0km2SXJJk8yRrJDk1ybO6jlOSJGnYepOkJfl9mjHQnlxVuwD3An8EfBA4BHgrcGFVfbu7KCVJkkajTzcOPB3YDfhhEoB1gWur6uAkrwD2B3aZ6oVJ9gP2A9hki4eOJlpJkqQh6lOSFuCIqnrnUjOT9YCHtZPzgNsmv7CqDgUOBXj4do9/QG1PSZKkcdOb053AicDeSbYESLJpkm1oTnd+DvgH4LAO45MkSRqZ3iRpVXUh8G7g20nOA74DzAf+APhgVX0OuCvJ67uLUpIkaTT6dLqTqjoWOHbS7D8cWP6y0UYkSZLUjV4labPhIRuvbWUASZI09npzulOSJEn3m3M9aTfedA9Hf/G6Wd3mq1++xaxuT5IkaXl62ZOW5PQkWyc5rutYJEmSutDLnrSqelLb3HvysiRrVdU9Iw5JkiRppPrak7Ykyfwk57fT+yb5QpL/BSwLJUmS5rxe9qRNY3dg56q6setAJEmShq2XPWnT+M50CVqS/ZIsSrLotltvGHVckiRJs26ckrTbp1tQVYdW1YKqWrDBhpuNMiZJkqShGKckTZIkabXR1yStJj1LkiStVnp340CSzYAbgYlnqupw4PDuopIkSRqtXiVpSbYGTgI+AxwNvGNFt7HpJmtZIUCSJI29XiVpVXU18Oh28p+6jEWSJKlLvUrSZsMtN93DN469fla29dx9Np+V7UiSJK2ovt448DtJTkqyoOs4JEmSRqn3SZokSdLqqDdJ2mCtznb6wCQHt5OvSHJWkouT7NlNhJIkSaPTmyRtOdaqqoXAW4CDug5GkiRp2MYlSftS+7wYmD954WDtzlut3SlJkuaAPiVp97B0PA8eaN/ZPt/LFHekDtbu3NDanZIkaQ7oU5J2DbBlks2SrAO8oOuAJEmSutKbcdKq6u4k7wV+AFwO/KTjkCRJkjrTmyQNoKo+Dnx8GcuvZ4pr0iRJkuaaXiVps2GjTdayUoAkSRp7fbomTZIkSa0515O25IZ7+P6R163SNp78ui1mKRpJkqSV06uetCRvSnJRks91HYskSVKX+taTdgDw3Kq6vOtAJEmSutSbnrQkhwCPAr6a5LYkG6dxQ5LXtet8Nskzuo1UkiRp+HqTpFXV/sDVwFOBzwFPBnYELgMmiqr/IXBmJwFKkiSNUG+StElOBZ7SPj4F7JTkocCNVbVk8sqDtTtvvs3anZIkafz1NUk7hab3bE/gJOA6YG+a5O0BBmt3bryBtTslSdL462WSVlW/ADYHtq+qy4DTgAOZJkmTJEmaa3qZpLV+AFzctk8FHkqTrEmSJM15vRqCo6rmD7T/ZKB9Ov1OKCVJkmZVr5K02TBvs7WsGCBJksaevVOSJEk9NOd60u647h7OO/TalXrtzvttOcvRSJIkrRx70iRJknqod0lakgcMVitJkrS66VWSliTMIKYkc+40rSRJ0qDOk7Qk85NclOSTwNnAukk+kuTsJCcm2aJd76Qk/5LkZODNnQYtSZI0ZJ0naa0dgCOr6gnt9NlVtStwMnDQwHobV9UfVdVHBl88WLvzpiXW7pQkSeOvL0nalVV1Ztu+Dzi2bR8F7DGw3rFMYbB25ybzrN0pSZLGX1+StNuXsaxmuJ4kSdKc0ZckbdAawN5t+zVYr1OSJK2G+niX5O3AjkkWA7cA+3QcjyRJ0silqpa/1hhZsGBBLVq0qOswJEmSlivJ4qpaMNWyPp7ulCRJWu2ZpEmSJPVQH69JWyV3XXM3V3zs1yv0mvlv2WpI0UiSJK2c3vekJbkiyeZdxyFJkjRKvUrS0lhjYHrNLuORJEnqSudJ2hS1O+9N8t4kPwB2b1d7W5Kz2sd23UUrSZI0Gp0naa3JtTvPr6onVtXEQLa3VtVC4D+Aj01+8WDtzhtut3anJEkaf31J0gZrd94LfHHS8qMHnneftGyp2p2brW/tTkmSNP76kqQN1uT8bVXdO2l5TdOWJEmak/qSpC3PPgPPZ3QZiCRJ0iiMyzhp67Q3EqwBvLrrYCRJkobN2p2SJEkdsXanJEnSmDFJkyRJ6qFxuSZtxu7+9Z38+kOXz3j9rd72yCFGI0mStHJ60ZOWZMk08+cnOX/U8UiSJHWtF0naVKzbKUmSVme9StKS7JXke0k+D/y4nb1WkiOSnJfkuCTrdRmjJEnSKPQqSWstBN5VVY9tp3cADq2qnYFbgQMmv2Dp2p03jjBUSZKk4ehjknZWVQ1e+f+Lqvp+2z4K2GPyC5au3bnpSIKUJEkapj4mabdPmp482u7cGn1XkiRpCn1M0iZ7RJLd2/argdO6DEaSJGkUxiFJuwj40yTnAZsCn+o4HkmSpKGzdqckSVJHrN0pSZI0ZkzSJEmSemju1e685g6u+eh5M1r3IX+z85CjkSRJWjm97klrKxCcMNB+UtcxSZIkjUKvk7RJ9gJM0iRJ0mqhsyQtyfwkP5lclzPJc9r5pwEvm1gX2B/4myTnJNmzq7glSZJGoeuetMl1Of8WOAx4IbAnsBVAVV0BHAJ8tKp2qapTuwlXkiRpNLpO0ibX5VwAXF5Vl1QzgNtRM9nIYIH1G2+/aVixSpIkjUzXSdrkkXQ3mmLe8jcyUGB90/U3mZ3IJEmSOtR1kja5Lud3gUcm2XZg3oTbgA1GGZwkSVJXuk7SJtfl/CiwH/C19saBKwfW/V/gpd44IEmSVgddD2Z7X1XtP2neN4HHTF6xqi4Gljv67NoPWddBaiVJ0tjruidNkiRJU+isJ60dVuNxXe1fkiSpz7o+3Tnr7r72dq759zOWuc5D3rz7MpdLkiR1rVenO5Ms6ToGSZKkPuhNkpYk9CgeSZKkLnWaFLX1Oy9K8kngbGDdJB9JcnaSE5Ns0a73piQXtjU+j+kyZkmSpFHoQ8/VDsCRVfWEdvrsqtoVOBk4qJ33DuAJbY3PyUN2SJIkzTl9SNKurKoz2/Z9wLFt+yhgj7Z9HvC5JH8M3DN5A0vV7lxi7U5JkjT++pCk3b6MZRN1PJ8PfALYDVicZKm7Upeq3TnP2p2SJGn89SFJG7QGsHfbfg1wWpI1gIdX1feAtwMbA/M6ik+SJGkk+jZO2u3AjkkWA7cA+wBrAkcl2QgI8NGqurnDGCVJkoYuVbX8tcbIggULatGiRV2HIUmStFxJFlfVgqmW9e10pyRJkjBJkyRJ6qW+XZO2yu659lau/X/fnXb5ln/9jBFGI0mStHJ625NmHU9JkrQ6622SJkmStDrrfZKW5PeSnJLknCTnJ9mz65gkSZKGbRyuSXsN8K2q+uckawLrdR2QJEnSsI1DkvZD4L+SrA18uarOmbxCkv2A/QAetsmWIw5PkiRp9vX+dGdVnQI8BbgK+GyS102xzu9qd242b6ORxyhJkjTbep+kJdkGuLaqDgP+E9i145AkSZKGbhxOd+4FvC3J3cAS4AE9aZIkSXNNb5O0qprXPh8BHNFxOJIkSSPV2yRtZa215YZWFZAkSWOv99ekSZIkrY7mXE/aPdfezLWf+Mq0y7f8yxePMBpJkqSVY0+aJElSD5mkSZIk9dBIkrQk6yf5WpJz2/qb+yQ5fmD5M5N8qW0vSfLBJIuTfDfJwiQnJbksyYtGEa8kSVLXRtWT9hzg6qp6fFU9Dvgm8PtJtmiXvx7477a9PnBSVe0G3Aa8D3gm8FLgvSOKV5IkqVOjStJ+DDyj7SHbs6puAT4L/HGSjYHdgW+0695Fk8RNvO7kqrq7bc+fauNJ9kuyKMmiG5bcOsz3IUmSNBIjubuzqi5OshvwPOD9Sb4NfAb4X+C3wBeq6p529burqtr2fcCd7TbuSzJlvFV1KHAowC6P2K6mWkeSJGmcjCRJS7I1cGNVHZVkCbBvVV2d5Grg3TSnMyVJktQa1ThpOwEfSnIfcDfwxnb+54AtqurCEcUhSZI0FkZ1uvNbwLemWLQHcNikdecNtA+ebpkkSdJc1lnFgSSLgduBt87mdtfacmOrCkiSpLGX+6/RnxuS3Ab8tOs4NHSbA9d3HYSGymM893mM5z6P8fJtU1VbTLVgztXuBH5aVQu6DkLDlWSRx3lu8xjPfR7juc9jvGosCyVJktRDJmmSJEk9NBeTtEO7DkAj4XGe+zzGc5/HeO7zGK+COXfjgCRJ0lwwF3vSJEmSxt5YJWlJnpPkp0kuTfKOKZavk+TYdvkPkswfWPbOdv5Pkzx7lHFr5lb2GCeZn+SOJOe0j0NGHbtmZgbH+ClJzk5yT5K9Jy370ySXtI8/HV3UWhGreIzvHfgef3V0UWtFzeA4/22SC5Ocl+TEJNsMLPO7PBNVNRYPYE3gZ8CjgAcB5wKPnbTOAcAhbftVwLFt+7Ht+usAj2y3s2bX78nHrB7j+cD5Xb8HH7NyjOcDOwNHAnsPzN8UuKx93qRtb9L1e/Ixe8e4Xbak6/fgY9aO81OB9dr2Gwd+X/tdnuFjnHrSFgKXVtVlVXUXcAwwubTAi4Ej2vZxwNOTpJ1/TFXdWVWXA5e221O/rMox1nhY7jGuqiuq6jzgvkmvfTbwnar6/9u78xCtqjiM498nK1sMtZII20wUqagRDaE0bUEqSI0SooVKixYKglaQCiRCkP6pKFooi4IWK7Gg1WVowXJ30vYyFEVBTVMrKn/9cc8b12nGebeZ9775fODy3ve859x7zj1zh9+c99w5WyNiG/AhcGFPVNoqUksfW/Mop58XRMTu9HYRcFza971cpmYK0gYC63Lv16e0DvNExF/AduCoMsta49XSxwCDJC2X1CppTHdX1qpSy73o+7g51NpPh0haImmRpEn1rZrVUaX9PBV4t8qy+61mWnGgo9GS9o+mdpannLLWeLX08UbghIjYImkEMEfSqRGxo96VtJrUci/6Pm4OtfbTCRGxQdLJwHxJbRHxQ53qZvVTdj9LuhoYCYyttOz+rplG0tYDx+feHwds6CyPpAOBvsDWMsta41Xdx+mr7C0AEbGUbK7E0G6vsVWqlnvR93FzqKmfImJDev0RWAgMr2flrG7K6mdJFwDTgAkR8UclZa25grTFwBBJgyQdTDZpvP2TP3OB0lMilwPzI5ulOBe4Ij0ZOAgYAnzRQ/W28lXdx5IGSOoFkP4CH0I2GdWKpZw+7sz7wHhJ/SX1B8anNCuWqvs49W3vtH80cDawpttqarXosp8lDQeeIgvQNuc+8r1crkY/uVDJBlwMfEs2SjItpU0n+wEAOAR4nezBgC+Ak3Nlp6Vy3wAXNbot3urbx8BlwGqyJ4yWAZc0ui3equ7jM8n+0t4FbAFW58pOSX3/PXB9o9virb59DJwFtKX7uA2Y2ui2eKupnz8CNgEr0jY3V9b3chmbVxwwMzMzK6Bm+rrTzMzMbL/hIM3MzMysgBykmZmZmRWQgzQzMzOzAnKQZmZmZlZADtLMrEdI+lvSitx2UhXH6Cfp1vrX7t/jXyfp8e46fifnnCTplJ48p5k1BwdpZtZTfouIlty2topj9AMqDtJK/+i4aNKqGZMAB2lm9h8O0sysYST1kjRT0mJJqyTdlNL7SJonaZmkNkkTU5EZwOA0EjdT0jhJ7+SO97ik69L+WkkPSPoEmCxpsKT3JC2V9LGkYV3UbZakJyUtkPSjpLGSnpP0laRZuXw7JT2S6jpP0oCU3pIWCV8l6a30n9WRtFDSw5JagXuBCcDM1KbBkm5M12OlpDckHZarz6OSPkv1uTxXh3vSdVopaUZKq6i9ZlY8zbTAupk1t0MlrUj7P0XEpcBUYHtEnJmWA/pU0gfAOuDSiNiRlgdaJGkucB9wWkS0AEga18U5f4+I0SnvPODmiPhO0ijgCeC8Lsr3T3kmAG+TLVN0A7BYUktErAAOB5ZFxJ2SHgAeBG4DXgRuj4hWSdNT+h3puP0iYmyq1xDgnYiYnd7/EhHPpP2H0jV6LJU7FhgNDCNbgme2pIvIRuNGRcRuSUemvE9X0V4zKxAHaWbWU34rBVc544HTc6NCfcnWXV0PPCzpHGAPMBA4popzvgrZyBzZkkOvSyp91ruM8m9HREhqAzZFRFs63mrgJLKlbvaUzgO8BLwpqS9ZINaa0l8gW85sr3p14rQUnPUD+rD3moZzImIPsEZS6XpcADwfEbsBImJrDe01swJxkGZmjSSy0aa9FldOX1kOAEZExJ+S1pKt29reX+w9baN9nl3p9QDglw6CxK78kV735PZL7zv7/VnOWnu79vHZLGBSRKxM12FcB/WB7NqVXtufs9r2mlmBeE6amTXS+8Atkg4CkDRU0uFkI2qbU4B2LnBiyv8rcESu/M/AKZJ6p9Gr8zs6SUTsAH6SNDmdR5LOqFMbDgBKI4FXAp9ExHZgm6QxKf0aoLWjwvy3TUcAG9M1uaqM838ATMnNXTuym9trZj3EQZqZNdKzwBpgmaQvgafIRqheBkZKWkIWqHwNEBFbyOatfSlpZkSsA14DVqUyy/dxrquAqZJWAquBifvIW4ldwKmSlpLN+Zqe0q8leyBgFdCSS2/vFeBuScslDQbuBz4HPiS1e18i4j2y+WlL0py/u9JH3dVeM+shiihnZN7MzDoiaWdE9Gl0Pczs/8cjaWZmZmYF5JE0MzMzswLySJqZmZlZATlIMzMzMysgB2lmZmZmBeQgzczMzKyAHKSZmZmZFZCDNDMzM7MC+geg5blLgbdDpwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# For POS-unigrams:\n",
    "model_type = 'pos-unigrams'\n",
    "X, _, feature_names = vectorizer.pos_unigrams(fnames, [], return_feature_names=True)\n",
    "\n",
    "print(\"Feature Names:\", feature_names)\n",
    "\n",
    "feat_imp = get_feat_imp(X)\n",
    "\n",
    "fi_df = plot_feature_importance(feature_names, feat_imp, model_type)\n",
    "fi_df.to_csv(feat_path+model_type+'.csv', index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Output accuracy: [0.69047619 0.63095238 0.69047619 0.80487805 0.7195122 ]\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x576 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# For Tense Mood Voice:\n",
    "model_type = 'tense-mood-voice'\n",
    "X, _ = vectorizer.tense_mood_voice(fnames, [])\n",
    "feature_names = ['temporality', 'temporal_order', 'setting', 'concreteness', 'saying', 'eventfulness', 'agenthood', 'agency', 'coherence', 'feltness']\n",
    "\n",
    "feat_imp = get_feat_imp(X)\n",
    "fi_df = plot_feature_importance(feature_names, feat_imp, model_type)\n",
    "fi_df.to_csv(feat_path+model_type+'.csv', index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
